Automated Revision Graphs – AIED 2020

I’ve recently had my writing analytics work published at the 21st international conference on artificial intelligence in education (AIED 2020) where the theme was “Augmented Intelligence to Empower Education”. It is a short paper describing a text analysis and visualisation method to study revisions. It introduced ‘Automated Revision Graphs’ to study revisions in short texts at a sentence level by visualising text as graph, with open source code.

Shibani A. (2020) Constructing Automated Revision Graphs: A Novel Visualization Technique to Study Student Writing. In: Bittencourt I., Cukurova M., Muldner K., Luckin R., Millán E. (eds) Artificial Intelligence in Education. AIED 2020. Lecture Notes in Computer Science, vol 12164. Springer, Cham. [pdf] https://doi.org/10.1007/978-3-030-52240-7_52

I did a short introductory video for the conference, which can be viewed below:

I also had another paper I co-authored on multi-modal learning analytics lead by Roberto Martinez, which received the best paper award in the conference. The main contribution of the paper is a set of conceptual mappings from x-y positional data (captured from sensors) to meaningful measurable constructs in physical classroom movements, grounded in the theory of Spatial Pedagogy. Great effort by the team!

Details of the second paper can be found here:

Martinez-Maldonado R., Echeverria V., Schulte J., Shibani A., Mangaroska K., Buckingham Shum S. (2020) Moodoo: Indoor Positioning Analytics for Characterising Classroom Teaching. In: Bittencourt I., Cukurova M., Muldner K., Luckin R., Millán E. (eds) Artificial Intelligence in Education. AIED 2020. Lecture Notes in Computer Science, vol 12163. Springer, Cham. [pdf] https://doi.org/10.1007/978-3-030-52237-7_29

Notes: Computational analysis of move structures in academic abstracts

Reference:

Wu, J. C., Chang, Y. C., Liou, H. C., & Chang, J. S. (2006, July). Computational analysis of move structures in academic abstracts. In Proceedings of the COLING/ACL on Interactive presentation sessions (pp. 41-44). Association for Computational Linguistics.

Background:

  • Swales pattern for research articles: Introduction, Methods, Results, Discussion (IMRD) and Creating a Research Space (CARS) model.
  • Studying the rhetorical structure of tests is found to be useful to aid reading and writing (Mover tool notes here).

Purpose:

  • To automatically analyze move structures (Background, Purpose, Method, Result, and Conclusion) from research article abstracts.
  • To develop an online learning system CARE (Concordancer for Academic wRiting in English) using move structures to help novice writers.

Method:

  • Processes involved:

care-system

  • TANGO Concordancer used for extracting collocations with chunking and clause information – Sample  Verb-Noun collocation structures in corpus: VP+NP, VP+PP+NP, and VP+NP+PP (Ref: Jian, J. Y., Chang, Y. C., & Chang, J. S. (2004, July). TANGO: Bilingual collocational concordancer. In Proceedings of the ACL 2004 on Interactive poster and demonstration sessions (p. 19). Association for Computational Linguistics.)
    • TANGO Tool accessible here.
  • Data: Corpus of 20,306 abstracts (95,960 sentences) from Citeseer. Manual tagging of moves in 106 abstracts containing 709 sentences. 72,708 collocation types extracted and manually tagged 317 collocations with moves.
  • Hidden Markov Model (HMM) trained using 115 abstracts containing 684 sentences.
  • Different parameters evaluated for the HMM model: “the frequency of collocation types, the number of sentences with collocation in each abstract, move sequence score and collocation score”

Results:

  • Precision of 80.54% achieved when 627 sentences were qualified with following parameters: weight of transitional probability function 0.7 , frequency threshold for a collocation to be applicable – 18 (crucial to exclude unreliable collocation).

Conclusion:

  • CARE system interface created for querying and looking up sentences for a specific move.
  • System is expected to help non native speakers write abstracts for research articles.